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A method for fitting a curve (not necessarily a straight line) through a set of points using some goodness-of-fit criterion. The most common type of regression is linear ...

The logistic equation (sometimes called the Verhulst model or logistic growth curve) is a model of population growth first published by Pierre Verhulst (1845, 1847). The ...

A regression that is linear in the unknown parameters used in the fit. The most common form of linear regression is least squares fitting. Least squares fitting of lines and ...

The continuous distribution with parameters m and b>0 having probability and distribution functions P(x) = (e^(-(x-m)/b))/(b[1+e^(-(x-m)/b)]^2) (1) D(x) = 1/(1+e^(-(x-m)/b)) ...

A regression giving conditional expectation values of a given variable in terms of two or more other variables.

The slope b of a line obtained using linear least squares fitting is called the regression coefficient.

Replacing the logistic equation (dx)/(dt)=rx(1-x) (1) with the quadratic recurrence equation x_(n+1)=rx_n(1-x_n), (2) where r (sometimes also denoted mu) is a positive ...

Conditional logit regression assumes a model of the form p_j=(e^(beta^'x_j))/(sum_(j)e^(beta^'x_j)) for j=1, ..., k+1. In this model, a subject is presented with choice ...

Loess local regression is a nonparametric technique for describing bivariate relationships where the functional form is not known in advance.

Self-recursion is a recursion that is defined in terms of itself, resulting in an ill-defined infinite regress. The formula for the volume of a cylinder leads to the ...